Contact Tracing Mobile Apps for COVID-19: Privacy Considerations and Related Trade-offs
Not on the map. Why?
Abstract (arXiv)
Contact tracing is an essential tool for public health officials and local communities to fight the spread of novel diseases, such as for the COVID-19 pandemic. The Singaporean government just released a mobile phone app, TraceTogether, that is designed to assist health officials in tracking down exposures after an infected individual is identified. However, there are important privacy implications of the existence of such tracking apps. Here, we analyze some of those implications and discuss ways of ameliorating the privacy concerns without decreasing usefulness to public health. We hope in writing this document to ensure that privacy is a central feature of conversations surrounding mobile contact tracing apps and to encourage community efforts to develop alternative effective solutions with stronger privacy protection for the users. Importantly, though we discuss potential modifications, this document is not meant as a formal research paper, but instead is a response to some of the privacy characteristics of direct contact tracing apps like TraceTogether and an early-stage Request for Comments to the community. Date written: 2020-03-24 Minor correction: 2020-03-30
Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). First posted on arXiv 25 Mar 2020.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2021: 3; 2022: 1; 2023: 2; 2024: 1; 2025: 1.
8 papers.
- 2021From Personalized Medicine to Population Health: A Survey of mHealth Sensing Techniquescited by 7
- 2023Protect Your Score: Contact Tracing With Differential Privacy Guaranteescited by 5
- 2021TB-ICT: A Trustworthy Blockchain-Enabled System for Indoor COVID-19 Contact Tracingcited by 3
- 2021Sentiment Analysis of Users' Reviews on COVID-19 Contact Tracing Apps with a Benchmark Datasetcited by 2
- 2022Differentially Private Learning of Hawkes Processescited by 1
- 2025HP-BERT: A framework for longitudinal study of Hinduphobia on social media via language modelscited by 1
- 2023Effectiveness of probabilistic contact tracing in epidemic containment: the role of super-spreaders and transmission path reconstructioncited by 0
- 2024Differential Privacy on Trust Graphscited by 0
- 2025HP-BERT: A framework for longitudinal study of Hinduphobia on social media via language models7 Jan 2025
- 2024Differential Privacy on Trust Graphs15 Oct 2024
- 2023Protect Your Score: Contact Tracing With Differential Privacy Guarantees18 Dec 2023
- 2023Effectiveness of probabilistic contact tracing in epidemic containment: the role of super-spreaders and transmission path reconstruction1 Dec 2023
- 2022Differentially Private Learning of Hawkes Processes27 Jul 2022
- 2021TB-ICT: A Trustworthy Blockchain-Enabled System for Indoor COVID-19 Contact Tracing9 Aug 2021
- 2021From Personalized Medicine to Population Health: A Survey of mHealth Sensing Techniques2 Jul 2021
- 2021Sentiment Analysis of Users' Reviews on COVID-19 Contact Tracing Apps with a Benchmark Dataset1 Mar 2021